CN109597825B - Rule engine calling method, device, equipment and computer readable storage medium - Google Patents
Rule engine calling method, device, equipment and computer readable storage medium Download PDFInfo
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- CN109597825B CN109597825B CN201811464439.4A CN201811464439A CN109597825B CN 109597825 B CN109597825 B CN 109597825B CN 201811464439 A CN201811464439 A CN 201811464439A CN 109597825 B CN109597825 B CN 109597825B
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Abstract
The invention discloses a rule engine calling method, which comprises the following steps: when a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode is received, acquiring an input Data Transmission Object (DTO) of a rule engine, and calling a preset engine function; calling a rule engine integrated in a data center of a big data platform through the engine function, and converting the DTO into a corresponding input business object model BOM; and inputting the input business object model BOM into the rule engine so that the rule engine outputs a corresponding output business object model BOM. The invention also discloses a rule engine calling device, equipment and a computer readable storage medium. The invention can improve the flexibility of the rule engine calling and reduce the time consumption of calculation.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a computer-readable storage medium for invoking a rule engine.
Background
With the continuous development of information technology, business management of enterprises depends on the realization of a rule engine. Currently, commonly used rule engines in the market include IlogJRules, drools, jess, visual Rules, and the like, and APIs (Application Programming Interface) provided by these rule engines are limited to Application calls and do not support SQL (Structured Query Language) calls, which results in that the rule engines generally need to be compiled into applications for use, and thus, the rule engines are poor in flexibility and the complexity of the rule engine usage is increased.
In addition, the existing rule engine calls all need to design specific input DTOs (Data Transfer objects) and output DTOs for rule packets, and an adaptation layer is developed to realize conversion from the DTOs to BOMs (Business Object models), which results in that the adaptation layer needs to be redefined when changing rules each time, and service extensibility is poor; moreover, because the existing rule calculation is outside the database, the application program needs to read the input table from the database to perform DTO-to-BOM conversion, then calls the rule engine, and then converts the output BOM of the rule engine into DTO to be written into the database, which involves the transfer of a large data volume and increases the calculation time consumption of the whole process.
Disclosure of Invention
The invention mainly aims to provide a rule engine calling method, a rule engine calling device, rule engine calling equipment and a computer readable storage medium, aiming at improving the flexibility of rule engine calling and reducing the time consumption of calculation.
In order to achieve the above object, the present invention provides a method for invoking a rule engine, comprising the steps of:
when a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode is received, acquiring an input Data Transmission Object (DTO) of a rule engine, and calling a preset engine function;
calling a rule engine integrated in a data center of a big data platform through the engine function, and converting the DTO into a corresponding input business object model BOM;
and inputting the input business object model BOM into the rule engine so that the rule engine outputs a corresponding output business object model BOM.
Preferably, the step of obtaining an input data transmission object DTO of the rules engine comprises:
reading corresponding service index data from a big data platform center according to a table structure of a preset rule engine input table;
and generating an input Data Transmission Object (DTO) of the rule engine according to the table structure of the rule engine input table and the service index data.
Preferably, after the step of inputting the input business object model BOM into the rule engine to enable the rule engine to output the corresponding output business object model BOM, the method further includes:
acquiring the output business object model BOM output by the rule engine;
generating a business rule result table according to a table structure of a preset rule engine output table and the output business object model BOM;
and storing the service rule result table to the big data platform data center.
Preferably, after the step of storing the business rule result table in the big data platform data center, the method further includes:
receiving a query instruction based on the business rule result table;
and inquiring a corresponding business rule result table according to the inquiry instruction to obtain an inquiry result.
Preferably, before the step of acquiring an input data transmission object DTO of the rule engine and calling a preset engine function when receiving a rule engine call request initiated by the client in a structured query language SQL manner, the method further includes:
defining a table structure of a rule engine input table and a table structure of a rule engine output table;
and storing the defined table structure of the rule engine input table and the defined table structure of the rule engine output table to the big data platform data center.
In order to achieve the above object, the present invention further provides a rule engine invoking device, including:
the acquisition module is used for acquiring an input data transmission object DTO of a rule engine and calling a preset engine function when receiving a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode;
the calling conversion module is used for calling a rule engine integrated in a data center of a big data platform through the engine function and converting the input data transmission object DTO into a corresponding input business object model BOM;
and the input module is used for inputting the input business object model BOM into the rule engine so as to enable the rule engine to output a corresponding output business object model BOM.
Preferably, the obtaining module is further configured to read corresponding service index data from a big data platform center according to a table structure of a preset rule engine input table; and generating an input Data Transmission Object (DTO) of the rule engine according to the table structure of the rule engine input table and the service index data.
Preferably, the apparatus further comprises:
the generating module is used for acquiring the output business object model BOM output by the rule engine; generating a business rule result table according to a table structure of a preset rule engine output table and the output business object model BOM;
and the storage module is used for storing the service rule result table to the big data platform data center.
Preferably, the apparatus further comprises:
the query module is used for receiving a query instruction based on the business rule result table; and inquiring a corresponding business rule result table according to the inquiry instruction to obtain an inquiry result.
Preferably, the apparatus further comprises:
the definition module is used for defining the table structure of the rule engine input table and the table structure of the rule engine output table; and storing the defined table structure of the rule engine input table and the defined table structure of the rule engine output table to the big data platform data center.
In addition, to achieve the above object, the present invention further provides a rule engine invoking device, including: a memory, a processor, and a rules engine caller stored on the memory and executable on the processor, the rules engine caller when executed by the processor implementing the steps of:
when a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode is received, acquiring an input Data Transmission Object (DTO) of a rule engine, and calling a preset engine function;
calling a rule engine integrated in a big data platform data center through the engine function, and converting the input data transmission object DTO into a corresponding input business object model BOM;
and inputting the input business object model BOM into the rule engine so that the rule engine outputs a corresponding output business object model BOM.
Preferably, the rules engine caller when executed by the processor further implements the steps of:
reading corresponding service index data from a big data platform center according to a table structure of a preset rule engine input table;
and generating an input data transmission object DTO of the rule engine according to the table structure of the rule engine input table and the service index data.
Preferably, the rules engine caller when executed by the processor further implements the steps of:
acquiring the output business object model BOM output by the rule engine;
generating a business rule result table according to a table structure of a preset rule engine output table and the output business object model BOM;
and storing the service rule result table to the big data platform data center.
Preferably, the rules engine caller when executed by the processor further implements the steps of:
receiving a query instruction based on the business rule result table;
and inquiring a corresponding business rule result table according to the inquiry instruction to obtain an inquiry result.
In addition, to achieve the above object, the present invention also provides a computer readable storage medium, on which a rule engine calling program is stored, and the rule engine calling program, when executed by a processor, implements the steps of the rule engine calling method as described above.
When a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode is received, acquiring an input Data Transmission Object (DTO) of a rule engine, and calling a preset engine function; calling a rule engine integrated in a big data platform data center through the engine function, and converting the input data transmission object DTO into a corresponding input business object model BOM; and inputting the input business object model BOM into the rule engine so that the rule engine outputs a corresponding output business object model BOM. By the method, the SQL-based calling of the rule engine is realized, the flexibility of calling of the rule engine is improved, the rule engine is integrated into a data center of a big data platform, data migration is reduced, and the parallel computing capability of big data can be utilized, so that the computing time is reduced.
Drawings
Fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a first embodiment of a rule engine invocation method according to the present invention;
FIG. 3 is a diagram illustrating the relationship between the levels of a rule engine in the prior art.
The implementation, functional features and advantages of the present invention will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The main solution of the embodiment of the invention is as follows: when a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode is received, acquiring an input Data Transmission Object (DTO) of a rule engine, and calling a preset engine function; calling a rule engine integrated in a data center of a big data platform through the engine function, and converting the DTO into a corresponding input business object model BOM; and inputting the input business object model BOM into the rule engine so that the rule engine outputs a corresponding output business object model BOM.
The API provided by the existing rule engine is limited to the calling of an application program, but not supported by SQL, which causes the rule engine to be compiled into the application program for use, and the rule engine has poor flexibility and increased complexity in use. In addition, all the existing rule engine calls need to design specific input DTOs (Data Transfer Object) and output DTOs for a rule package, and an adaptation layer is developed to realize conversion from the DTOs to BOM (Business Object Model), which causes that the adaptation layer needs to be redefined when the rules are changed every time, resulting in poor service extensibility; moreover, because the existing rule calculation is outside the database, the application program needs to read the input table from the database to perform DTO-to-BOM conversion, then calls the rule engine, and then converts the output BOM of the rule engine into DTO to write the DTO into the database.
According to the method, the SQL-based calling of the rule engine is realized, the calling flexibility of the rule engine is improved, the rule engine is integrated into a data center of a big data platform, data migration is reduced, the parallel computing capacity of big data can be utilized, and therefore computing time is reduced.
As shown in fig. 1, fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present invention.
The rule engine calling equipment in the embodiment of the invention can be a PC or a server with a big data platform.
As shown in fig. 1, the apparatus may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. The communication bus 1002 is used to implement connection communication among these components. The user interface 1003 may include a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration of the apparatus shown in fig. 1 is not intended to be limiting of the apparatus and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, the memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a rule engine calling program.
In the terminal shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to invoke a rules engine calling program stored in the memory 1005 and perform the following operations:
when a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode is received, acquiring an input Data Transmission Object (DTO) of a rule engine, and calling a preset engine function;
calling a rule engine integrated in a data center of a big data platform through the engine function, and converting the DTO into a corresponding input business object model BOM;
and inputting the input business object model BOM into the rule engine so that the rule engine outputs a corresponding output business object model BOM.
Further, the processor 1001 may call a rules engine calling program stored in the memory 1005, and also perform the following operations:
reading corresponding service index data from a big data platform center according to a table structure of a preset rule engine input table;
and generating an input Data Transmission Object (DTO) of the rule engine according to the table structure of the rule engine input table and the service index data.
Further, the processor 1001 may call a rules engine calling program stored in the memory 1005, and also perform the following operations:
acquiring the output business object model BOM output by the rule engine;
generating a business rule result table according to a table structure of a preset rule engine output table and the output business object model BOM;
and storing the service rule result table to the big data platform data center.
Further, the processor 1001 may call a rules engine calling program stored in the memory 1005, and also perform the following operations:
receiving a query instruction based on the business rule result table;
and querying a corresponding business rule result table according to the query instruction to obtain a query result.
Further, the processor 1001 may call a rules engine calling program stored in the memory 1005, and also perform the following operations:
defining a table structure of a rule engine input table and a table structure of a rule engine output table;
and storing the defined table structure of the rule engine input table and the defined table structure of the rule engine output table to the big data platform data center.
Based on the hardware structure, the embodiment of the rule engine calling method is provided.
Referring to fig. 2, fig. 2 is a schematic flowchart of a first embodiment of a rule engine invoking method according to the present invention, where the method includes:
step S10, when a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode is received, acquiring an input Data Transmission Object (DTO) of a rule engine, and calling a preset engine function;
in the prior art, the logic of an application program is generally divided into two parts: in the implementation of the program, the business rules are generally configured into rule files, and then the business rules are executed by calling a rule engine, so that only the rule files need to be changed when the business rules are changed, and the application program does not need to be re-developed.
In the prior art, a rule engine is mainly divided into an interface layer, an adaptation layer, a core, a data layer and a rule management layer. Referring to fig. 3, fig. 3 is a schematic diagram illustrating the relationship between the layers of the rule engine in the prior art. When an application program initiates a business decision, a rule engine is called through a rule engine calling interface, a data transmission object DTO is input to an adaptation layer, and the specific style of the DTO may be an xml (eXtensible Markup Language) document or a section of memory, a serialized object and the like; when the DTO passes through the adaptation layer, the adaptation layer is responsible for accessing other interfaces or a database to fill data, and then the input DTO is converted into an input BOM which can be identified by the rule engine and is input into the core of the rule engine; after the rule engine core obtains the input BOM, the object is transmitted into the operating context environment, then the rules are operated one by one, finally the output BOM of the operation result is obtained, and the intermediate possibly also passes through the adaptation layer and accesses the database filling data to become DTO and returns the DTO to the application program.
The difference of the method is that the rule engine is not integrated in an application program but integrated in a big data platform data center, and a client is supported to call the rule engine in an SQL mode. The big data platform can be a Spark platform which is a popular big data calculation and statistics platform at present, and various machine learning and data mining can be realized by calculating and counting the big data; the big data platform data center may be hive, spark sql, etc.
When a rule engine calling request initiated by a client in an SQL mode is received, the input DTO of the rule engine is obtained, and a preset engine function is called.
As an embodiment, the step of obtaining an input data transmission object DTO of the rule engine may include: reading corresponding service index data from a big data platform center according to a table structure of a preset rule engine input table; and generating an input Data Transmission Object (DTO) of the rule engine according to the table structure of the rule engine input table and the service index data.
The big data platform data center stores a table structure of a preset rule engine input table, and the input DTO of the rule engine can be generated by reading table data, namely service index data, corresponding to the table structure of the rule engine input table from the big data platform data center. In addition, the big data platform data center also stores a preset engine function, and the engine function is a user-defined function and is used for realizing the calling of the rule engine.
Step S20, calling a rule engine integrated in a data center of a big data platform through the engine function, and converting the input data transmission object DTO into a corresponding input business object model BOM;
in the step, a rule engine integrated in a data center of a big data platform is called through the engine function, namely, the engine function initiates a service decision API call to call the rule engine; and meanwhile, converting the input DTO into a corresponding input BOM for the rule engine to identify.
And S30, inputting the input business object model BOM into the rule engine so that the rule engine outputs a corresponding output business object model BOM.
In the step, the input BOM is input to a rule engine, and the rule engine calls a preset rule packet to perform rule processing, so that the output BOM is finally obtained. Therefore, the business processing by calling the rule engine is realized.
It should be noted that the rule engine may be integrated in a database of the big data platform, besides the big data platform data center, the database includes, but is not limited to, mysql, sql server, oracle, and the like.
In this embodiment, when a rule engine call request initiated by a client in a Structured Query Language (SQL) manner is received, an input Data Transmission Object (DTO) of a rule engine is acquired, and a preset engine function is called; calling a rule engine integrated in a data center of a big data platform through the engine function, and converting the DTO into a corresponding input business object model BOM; and inputting the input business object model BOM into the rule engine so that the rule engine outputs a corresponding output business object model BOM. By the method, the SQL-based calling of the rule engine is realized, the flexibility of calling of the rule engine is improved, the rule engine is integrated into a data center of a big data platform, data migration is reduced, the parallel computing capacity of big data can be utilized, and therefore computing time is reduced.
Further, based on the first embodiment of the rule engine calling method of the present invention, a second embodiment of the rule engine calling method of the present invention is provided.
In this embodiment, after the step of inputting the input business object model BOM into the rule engine to enable the rule engine to output the corresponding output business object model BOM, the method may further include: acquiring the output business object model BOM output by the rule engine; generating a business rule result table according to a table structure of a preset rule engine output table and the output business object model BOM; and storing the service rule result table to the big data platform data center.
Specifically, the big data platform can obtain an output BOM of the rule engine, obtain a table structure of a preset rule engine output table, and generate a service rule result table according to the obtained output BOM of the rule engine and the table structure of the preset rule engine output table, specifically, firstly, convert the output BOM into an output data transmission object DTO, and then generate a service rule result table according to the output DTO and the table structure of the rule engine output table; and then, storing the business rule result table as a record to a big data platform data center for subsequent viewing and calling.
Further, after the step of storing the business rule result table in the big data platform data center, the method may further include: receiving a query instruction based on the business rule result table; and querying a corresponding business rule result table according to the query instruction to obtain a query result.
Because the service logic and the service rule are independent, after the service rule result table is obtained, the service logic can initiate a query instruction for the service rule result table, the big data platform receives the query instruction, and queries the corresponding service rule result table according to the query instruction so as to obtain a query result and return the query result to the service logic. In this way, normal execution of business logic is guaranteed.
Further, before the step of acquiring the input data transmission object DTO of the rule engine and calling the preset engine function when receiving a rule engine call request initiated by the client in the structured query language SQL manner, the method may further include: defining a table structure of a rule engine input table and a table structure of a rule engine output table; and storing the defined table structure of the rule engine input table and the defined table structure of the rule engine output table to the big data platform data center.
In this embodiment, a developer may define, in advance, a table structure of the rule engine input table and a table structure of the rule engine output table in the big data platform according to actual business requirements, and the big data platform stores the defined table structure of the rule engine input table and the defined table structure of the rule engine output table in its own data center, thereby providing a precondition guarantee for subsequent invocation of the rule engine.
The invention also provides a rule engine calling device. The invention discloses a rule engine calling device, which comprises:
the acquisition module is used for acquiring an input data transmission object DTO of a rule engine and calling a preset engine function when receiving a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode;
the calling conversion module is used for calling a rule engine integrated in a data center of a big data platform through the engine function and converting the input data transmission object DTO into a corresponding input business object model BOM;
and the input module is used for inputting the input business object model BOM into the rule engine so as to enable the rule engine to output a corresponding output business object model BOM.
Further, the obtaining module is further configured to read corresponding service index data from a big data platform center according to a table structure of a preset rule engine input table; and generating an input Data Transmission Object (DTO) of the rule engine according to the table structure of the rule engine input table and the service index data.
Further, the apparatus further comprises:
the generating module is used for acquiring the output business object model BOM output by the rule engine; generating a business rule result table according to a table structure of a preset rule engine output table and the output business object model BOM;
and the storage module is used for storing the service rule result table to the big data platform data center.
Further, the apparatus further comprises:
the query module is used for receiving a query instruction based on the service rule result table; and querying a corresponding business rule result table according to the query instruction to obtain a query result.
Further, the apparatus further comprises:
the definition module is used for defining the table structure of the rule engine input table and the table structure of the rule engine output table; and storing the defined table structure of the rule engine input table and the defined table structure of the rule engine output table to the big data platform data center.
The operations executed by the program modules can refer to the embodiment of the rule engine calling method of the present invention, and are not described herein again.
The invention also provides a rule engine calling device.
The rule engine calling device of the invention comprises: a memory, a processor, and a rules engine caller stored on the memory and executable on the processor, the rules engine caller when executed by the processor implementing the steps of the rules engine calling method as described above.
The method implemented when the rule engine calling program running on the processor is executed may refer to each embodiment of the rule engine calling method of the present invention, and details are not described herein again.
The invention also provides a computer readable storage medium.
The computer readable storage medium of the present invention has stored thereon a rules engine invoking program which, when executed by a processor, implements the steps of the rules engine invoking method as described above.
The method implemented when the rule engine calling program running on the processor is executed may refer to each embodiment of the rule engine calling method of the present invention, and details are not described here.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or system comprising the element.
The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.
Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method of the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but in many cases, the former is a better implementation. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (12)
1. A method for calling a rule engine, comprising the steps of:
when a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode is received, acquiring an input Data Transmission Object (DTO) of a rule engine, and calling a preset engine function;
calling a rule engine integrated in a data center of a big data platform through the engine function, and converting the DTO into a corresponding input business object model BOM;
and inputting the input business object model BOM into the rule engine so that the rule engine outputs a corresponding output business object model BOM.
2. The rules engine call method of claim 1, wherein the step of obtaining the input data transfer object DTO of the rules engine comprises:
reading corresponding service index data from a big data platform center according to a table structure of a preset rule engine input table;
and generating an input data transmission object DTO of the rule engine according to the table structure of the rule engine input table and the service index data.
3. The method for invoking rules engine of claim 1, wherein after the step of inputting the input business object model BOM into the rules engine to cause the rules engine to output a corresponding output business object model BOM, further comprising:
acquiring the output business object model BOM output by the rule engine;
generating a business rule result table according to a table structure of a preset rule engine output table and the output business object model BOM;
and storing the service rule result table to the big data platform data center.
4. The rules engine invocation method of claim 3, wherein after the step of storing the business rule result table in the big data platform data center, further comprising:
receiving a query instruction based on the business rule result table;
and querying a corresponding business rule result table according to the query instruction to obtain a query result.
5. The method for calling a rule engine according to claim 3 or 4, wherein before the step of obtaining the input data transmission object DTO of the rule engine and calling the preset engine function when receiving a rule engine calling request initiated by the client in the Structured Query Language (SQL), the method further comprises:
defining a table structure of a rule engine input table and a table structure of a rule engine output table;
and storing the defined table structure of the rule engine input table and the defined table structure of the rule engine output table to the big data platform data center.
6. A rule engine invoking device, wherein said rule engine invoking device comprises:
the acquisition module is used for acquiring an input data transmission object DTO of a rule engine and calling a preset engine function when receiving a rule engine calling request initiated by a client in a Structured Query Language (SQL) mode;
the calling conversion module is used for calling a rule engine integrated in a data center of a big data platform through the engine function and converting the input data transmission object DTO into a corresponding input business object model BOM;
and the input module is used for inputting the input business object model BOM into the rule engine so as to enable the rule engine to output the corresponding output business object model BOM.
7. The rules engine invocation device according to claim 6,
the acquisition module is also used for reading corresponding service index data from the big data platform center according to a table structure of a preset rule engine input table; and generating an input Data Transmission Object (DTO) of the rule engine according to the table structure of the rule engine input table and the service index data.
8. The rules engine invocation device of claim 6, wherein said device further comprises:
the generating module is used for acquiring the output business object model BOM output by the rule engine; generating a business rule result table according to a table structure of a preset rule engine output table and the output business object model BOM;
and the storage module is used for storing the service rule result table to the big data platform data center.
9. The rules engine invocation device of claim 8, wherein said device further comprises:
the query module is used for receiving a query instruction based on the business rule result table; and querying a corresponding business rule result table according to the query instruction to obtain a query result.
10. The rules engine invocation device according to claim 8 or 9, wherein the device further comprises:
the definition module is used for defining the table structure of the rule engine input table and the table structure of the rule engine output table; and storing the defined table structure of the rule engine input table and the defined table structure of the rule engine output table to the big data platform data center.
11. A rules engine invoking device, wherein the rules engine invoking device comprises: memory, a processor and a rules engine caller stored on the memory and executable on the processor, the rules engine caller when executed by the processor implementing the steps of the rules engine call method as claimed in any one of claims 1 to 5.
12. A computer readable storage medium having stored thereon a rules engine caller which when executed by a processor implements the steps of the rules engine call method of any of claims 1 to 5.
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